{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,24]],"date-time":"2026-03-24T16:06:28Z","timestamp":1774368388136,"version":"3.50.1"},"reference-count":46,"publisher":"Springer Science and Business Media LLC","issue":"9","license":[{"start":{"date-parts":[[2022,1,21]],"date-time":"2022-01-21T00:00:00Z","timestamp":1642723200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2022,1,21]],"date-time":"2022-01-21T00:00:00Z","timestamp":1642723200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Neural Comput & Applic"],"published-print":{"date-parts":[[2022,5]]},"DOI":"10.1007\/s00521-021-06726-9","type":"journal-article","created":{"date-parts":[[2022,1,21]],"date-time":"2022-01-21T00:04:01Z","timestamp":1642723441000},"page":"7311-7324","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":74,"title":["Mango leaf disease identification and classification using a CNN architecture optimized by crossover-based levy flight distribution algorithm"],"prefix":"10.1007","volume":"34","author":[{"given":"M.","family":"Prabu","sequence":"first","affiliation":[]},{"given":"Balika J.","family":"Chelliah","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2022,1,21]]},"reference":[{"key":"6726_CR1","doi-asserted-by":"crossref","unstructured":"Hossain E, Hossain Md F, AnisurRahaman M (2019) A color and texture based approach for the detection and classification of plant leaf disease using KNN classifier. In: 2019 international conference on electrical, computer and communication engineering (ECCE). IEEE, pp 1\u20136","DOI":"10.1109\/ECACE.2019.8679247"},{"key":"6726_CR2","unstructured":"Prakash B, Yerpude A (2015) Identification of mango leaf disease and control prediction using image processing and neural network. Int J Sci Res Dev, 3(5)."},{"issue":"6","key":"6726_CR3","doi-asserted-by":"publisher","first-page":"667","DOI":"10.1094\/PHYTO-96-0667","volume":"96","author":"WFO Marasas","year":"2006","unstructured":"Marasas WFO, Ploetz RC, Wingfield MJ, Wingfield BD, Steenkamp ET (2006) Mango malformation disease and the associated Fusarium species. Phytopathology 96(6):667\u2013672","journal-title":"Phytopathology"},{"issue":"1","key":"6726_CR4","doi-asserted-by":"publisher","first-page":"43","DOI":"10.5815\/ijmecs.2017.01.05","volume":"9","author":"SB Ullagaddi","year":"2017","unstructured":"Ullagaddi SB, Viswanadha Raju S (2017) Automatic robust segmentation scheme for pathological problems in mango crop. Int J Modern Educ Comput Sci 9(1):43","journal-title":"Int J Modern Educ Comput Sci"},{"key":"6726_CR5","doi-asserted-by":"publisher","first-page":"57","DOI":"10.1016\/j.compag.2012.11.009","volume":"91","author":"B Payne Alison","year":"2013","unstructured":"Payne Alison B, Walsh KB, Subedi PP, Jarvis D (2013) Estimation of mango crop yield using image analysis\u2013segmentation method. Comput Electron Agric 91:57\u201364","journal-title":"Comput Electron Agric"},{"key":"6726_CR6","doi-asserted-by":"publisher","first-page":"277","DOI":"10.1016\/j.cose.2018.04.009","volume":"77","author":"V Sundararaj","year":"2018","unstructured":"Sundararaj V, Muthukumar S, Kumar RS (2018) An optimal cluster formation based energy efficient dynamic scheduling hybrid MAC protocol for heavy traffic load in wireless sensor networks. Comput Secur 77:277\u2013288","journal-title":"Comput Secur"},{"issue":"3","key":"6726_CR7","doi-asserted-by":"publisher","first-page":"117","DOI":"10.22266\/ijies2016.0930.12","volume":"9","author":"V Sundararaj","year":"2016","unstructured":"Sundararaj V (2016) An efficient threshold prediction scheme for wavelet based ECG signal noise reduction using variable step size firefly algorithm. International Journal of Intelligent Engineering and Systems 9(3):117\u2013126","journal-title":"International Journal of Intelligent Engineering and Systems"},{"issue":"4","key":"6726_CR8","doi-asserted-by":"publisher","first-page":"325","DOI":"10.1504\/IJBET.2019.103242","volume":"31","author":"V Sundararaj","year":"2019","unstructured":"Sundararaj V (2019) Optimised denoising scheme via opposition-based self-adaptive learning PSO algorithm for wavelet-based ECG signal noise reduction. Int J Biomed Eng Technol 31(4):325","journal-title":"Int J Biomed Eng Technol"},{"issue":"11","key":"6726_CR9","doi-asserted-by":"publisher","first-page":"1128","DOI":"10.1002\/pip.3315","volume":"28","author":"V Sundararaj","year":"2020","unstructured":"Sundararaj V, Anoop V, Dixit P, Arjaria A, Chourasia U, Bhambri P, Rejeesh MR, Sundararaj R (2020) CCGPA-MPPT: Cauchy preferential crossover-based global pollination algorithm for MPPT in photovoltaic system. Prog Photovoltaics Res Appl 28(11):1128\u20131145","journal-title":"Prog Photovoltaics Res Appl"},{"issue":"4","key":"6726_CR10","first-page":"1","volume":"38","author":"S Ravikumar","year":"2021","unstructured":"Ravikumar S, Kavitha D (2021) CNN-OHGS: CNN-oppositional-based Henry gas solubility optimization model for autonomous vehicle control system. J Field Robot. 38(4):1\u201330","journal-title":"J Field Robot."},{"key":"6726_CR11","first-page":"1","volume":"12","author":"S Ravikumar","year":"2020","unstructured":"Ravikumar S, Kavitha D (2020) IoT based home monitoring system with secure data storage by Keccak-Chaotic sequence in cloud server. J Ambient Intell Humaniz Comput 12:1\u201313","journal-title":"J Ambient Intell Humaniz Comput"},{"issue":"16","key":"6726_CR12","doi-asserted-by":"publisher","first-page":"22691","DOI":"10.1007\/s11042-019-7577-5","volume":"78","author":"MR Rejeesh","year":"2019","unstructured":"Rejeesh MR (2019) Interest point based face recognition using adaptive neuro fuzzy inference system. Multimed Tools Appl 78(16):22691\u201322710","journal-title":"Multimed Tools Appl"},{"issue":"1","key":"6726_CR13","doi-asserted-by":"crossref","first-page":"e4132","DOI":"10.1002\/ett.4132","volume":"32","author":"D Kavitha","year":"2021","unstructured":"Kavitha D, Ravikumar S (2021) IOT and context-aware learning-based optimal neural network model for real-time health monitoring. Trans Emerging Telecommun Technol 32(1):e4132","journal-title":"Trans Emerging Telecommun Technol"},{"key":"6726_CR14","doi-asserted-by":"publisher","first-page":"105046","DOI":"10.1016\/j.dib.2019.105046","volume":"28","author":"BA Hassan","year":"2020","unstructured":"Hassan BA, Rashid TA (2020) Datasets on statistical analysis and performance evaluation of backtracking search optimisation algorithm compared with its counterpart algorithms. Data Brief 28:105046","journal-title":"Data Brief"},{"key":"6726_CR15","doi-asserted-by":"crossref","unstructured":"Hassan BA (2020) CSCF: a chaotic sine cosine firefly algorithm for practical application problems. Neural Comput Appl, pp1\u201320","DOI":"10.1007\/s00521-020-05474-6"},{"key":"6726_CR16","doi-asserted-by":"crossref","unstructured":"Hassan BA, Rashid TA, Mirjalili S (2021) Formal context reduction in deriving concept hierarchies from corpora using adaptive evolutionary clustering algorithm star. Complex Intell Syst, pp1\u201316","DOI":"10.1007\/s40747-021-00422-w"},{"key":"6726_CR17","first-page":"430","volume":"6","author":"KS Haseena","year":"2014","unstructured":"Haseena KS, Anees S, Madheswari N (2014) Power optimization using EPAR protocol in MANET. Int J Innov Sci Eng Technol 6:430\u2013436","journal-title":"Int J Innov Sci Eng Technol"},{"issue":"2","key":"6726_CR18","doi-asserted-by":"publisher","first-page":"971","DOI":"10.1007\/s10115-018-1263-1","volume":"60","author":"MM Gowthul Alam","year":"2019","unstructured":"Gowthul Alam MM, Baulkani S (2019) Local and global characteristics-based kernel hybridization to increase optimal support vector machine performance for stock market prediction. Knowl Inf Syst 60(2):971\u20131000","journal-title":"Knowl Inf Syst"},{"issue":"3","key":"6726_CR19","first-page":"299","volume":"12","author":"MM Gowthul Alam","year":"2017","unstructured":"Gowthul Alam MM, Baulkani S (2017) Reformulated query-based document retrieval using optimised kernel fuzzy clustering algorithm. Int J Bus Intell Data Min 12(3):299","journal-title":"Int J Bus Intell Data Min"},{"issue":"4","key":"6726_CR20","doi-asserted-by":"publisher","first-page":"1079","DOI":"10.1007\/s00500-018-3124-y","volume":"23","author":"MM Gowthul Alam","year":"2019","unstructured":"Gowthul Alam MM, Baulkani S (2019) Geometric structure information based multi-objective function to increase fuzzy clustering performance with artificial and real-life data. Soft Comput 23(4):1079\u20131098","journal-title":"Soft Comput"},{"issue":"1","key":"6726_CR21","first-page":"45","volume":"22","author":"S Nisha","year":"2016","unstructured":"Nisha S, Madheswari AN (2016) Secured authentication for internet voting in corporate companies to prevent phishing attacks. Int J Emerging Technol Comput Sci Electron 22(1):45\u201349","journal-title":"Int J Emerging Technol Comput Sci Electron"},{"key":"6726_CR22","doi-asserted-by":"crossref","unstructured":"Ullagaddi SB, Viswanadha Raju S (2017) An enhanced feature extraction technique for diagnosis of pathological problems in mango crop. Int J Image Graph Signal Process, 9(9).","DOI":"10.5815\/ijigsp.2017.09.04"},{"issue":"3","key":"6726_CR23","doi-asserted-by":"publisher","first-page":"185","DOI":"10.1007\/s42044-020-00057-z","volume":"3","author":"MM Rasel","year":"2020","unstructured":"Rasel MM, Roy S, Das SK, Rahman MA (2020) Mango leaf disease recognition using neural network and support vector machine. Iran J Comput Sci 3(3):185\u2013193","journal-title":"Iran J Comput Sci"},{"key":"6726_CR24","doi-asserted-by":"crossref","unstructured":"Kumari Neeraj, Ashutosh Kr Bhatt, Rakesh Kr Dwivedi, Rajendra Belwal (2020) Hybridized approach of image segmentation in classification of fruit mango using BPNN and discriminant analyzer. Multimedia Tools and Applications, pp.1\u201331.","DOI":"10.1007\/s11042-020-09747-z"},{"key":"6726_CR25","doi-asserted-by":"crossref","unstructured":"Kusrini, K, S Suputa, A Setyanto, Made Artha Agastya I, Herlambang Priantoro, Krishna Chandramouli, EbroulIzquierdo (2020) Data augmentation for automated pest classification in Mango farms. Computers and Electronics in Agriculture 179: 105842.","DOI":"10.1016\/j.compag.2020.105842"},{"key":"6726_CR26","doi-asserted-by":"publisher","first-page":"43721","DOI":"10.1109\/ACCESS.2019.2907383","volume":"7","author":"SU Pratap","year":"2019","unstructured":"Pratap SU, Chouhan SS, Jain S, Jain S (2019) Multilayer convolution neural network for the classification of mango leaves infected by anthracnose disease. IEEE Access 7:43721\u201343729","journal-title":"IEEE Access"},{"key":"6726_CR27","doi-asserted-by":"publisher","first-page":"189960","DOI":"10.1109\/ACCESS.2020.3031914","volume":"8","author":"TN Pham","year":"2020","unstructured":"Pham TN, Van Tran Ly, Truong SV, Dao, (2020) Early disease classification of mango leaves using feed-forward neural network and hybrid metaheuristic feature selection. IEEE Access 8:189960\u2013189973","journal-title":"IEEE Access"},{"key":"6726_CR28","unstructured":"Nathaniel, Edwin, Jesusimo, Rhowel M. Dellosa, (2019) Identification of mango leaves using artificial intelligence. Int J Sci Technol Res, 8(12)"},{"issue":"6","key":"6726_CR29","first-page":"11067","volume":"120","author":"S Arivazhagan","year":"2018","unstructured":"Arivazhagan S, VinethLigi S (2018) Mango leaf diseases identification using convolutional neural network. Int J Pure Appl Math 120(6):11067\u201311079","journal-title":"Int J Pure Appl Math"},{"key":"6726_CR30","doi-asserted-by":"crossref","unstructured":"Srunitha K, Bharathi D (2018) Mango leaf unhealthy region detection and classification. In Computational vision and bio inspired computing. Springer, Cham, pp. 422\u2013436","DOI":"10.1007\/978-3-319-71767-8_35"},{"key":"6726_CR31","first-page":"1982","volume":"25","author":"S Mishra","year":"2021","unstructured":"Mishra S, Ellappan V, Satapathy S, Dengia G, Mulatu BT, Tadele F (2021) Identification and classification of mango leaf disease using wavelet transform based segmentation and wavelet neural network model. Ann Roman Soc Cell Biol 25:1982\u20131989","journal-title":"Ann Roman Soc Cell Biol"},{"key":"6726_CR32","doi-asserted-by":"crossref","unstructured":"Deeba K, Amutha B (2020) ResNet-deep neural network architecture for leaf disease classification. Microprocess Microsyst, pp 103364","DOI":"10.1016\/j.micpro.2020.103364"},{"key":"6726_CR33","doi-asserted-by":"crossref","unstructured":"Tm P, Pranathi A, SaiAshritha K, Chittaragi NB, Koolagudi SG (2018, August) Tomato leaf disease detection using convolutional neural networks. In: 2018 Eleventh international conference on contemporary computing (IC3). IEEE, pp 1\u20135","DOI":"10.1109\/IC3.2018.8530532"},{"key":"6726_CR34","doi-asserted-by":"publisher","first-page":"220","DOI":"10.1016\/j.compag.2018.04.023","volume":"150","author":"S Muhammad","year":"2018","unstructured":"Muhammad S, Khan MA, Iqbal Z, Azam MF, M. Ikram Ullah Lali, Muhammad Younus Javed, (2018) Detection and classification of citrus diseases in agriculture based on optimized weighted segmentation and feature selection. Comput Electron Agric 150:220\u2013234","journal-title":"Comput Electron Agric"},{"issue":"1\u20133","key":"6726_CR35","first-page":"5","volume":"30","author":"M Marcin","year":"2016","unstructured":"Marcin M, Szczotka W (2016) Quenched trap model for L\u00e9vy flights. Commun Nonlinear Sci Numer Simul 30(1\u20133):5\u201314","journal-title":"Commun Nonlinear Sci Numer Simul"},{"key":"6726_CR36","doi-asserted-by":"crossref","unstructured":"Dutta S, Banerjee A (2020) Optimal image fusion algorithm using modified grey wolf optimization amalgamed with cuckoo search, levy fly and Mantegna algorithm. In 2020 2nd international conference on innovative mechanisms for industry applications (ICIMIA). IEEE, pp 284\u2013290","DOI":"10.1109\/ICIMIA48430.2020.9074959"},{"key":"6726_CR37","doi-asserted-by":"crossref","unstructured":"Sandler Mark, Andrew Howard, Menglong Zhu, Andrey Zhmoginov, and Liang-Chieh Chen (2018) Mobilenetv2: Inverted residuals and linear bottlenecks. In Proceedings of the IEEE conference on computer vision and pattern recognition, pp. 4510\u20134520.","DOI":"10.1109\/CVPR.2018.00474"},{"issue":"1","key":"6726_CR38","doi-asserted-by":"publisher","first-page":"595","DOI":"10.3906\/elk-1801-157","volume":"27","author":"S Imran","year":"2019","unstructured":"Imran S, Chaudhuri D (2019) A multiseed-based SVM classification technique for training sample reduction. Turk J Electr Eng Comput Sci 27(1):595\u2013604","journal-title":"Turk J Electr Eng Comput Sci"},{"key":"6726_CR39","unstructured":"Tharwat A (2018) Classification assessment methods, Appl. Comput. Inf."},{"key":"6726_CR40","doi-asserted-by":"crossref","unstructured":"Goutte C, Gaussier E (2005) A probabilistic interpretation of precision, recall and f-score, with implication for evaluation. In: Proceedings of European conference on information retrieval, Springer, Berlin, pp 345\u2013359","DOI":"10.1007\/978-3-540-31865-1_25"},{"key":"6726_CR41","doi-asserted-by":"crossref","unstructured":"Ting KM (2011) Confusion matrix. In: Encyclopedia of machine learning, Springer, Boston, p. 209","DOI":"10.1007\/978-0-387-30164-8_157"},{"key":"6726_CR42","unstructured":"National Mango Database. (n.d.). Retrieved from https:\/\/mangifera.res.in\/"},{"key":"6726_CR43","doi-asserted-by":"publisher","first-page":"105925","DOI":"10.1016\/j.asoc.2019.105925","volume":"86","author":"W Guo","year":"2020","unstructured":"Guo W, Liu T, Dai F, Xu P (2020) An improved whale optimization algorithm for forecasting water resources demand. Appl Soft Comput 86:105925","journal-title":"Appl Soft Comput"},{"issue":"15","key":"6726_CR44","doi-asserted-by":"publisher","first-page":"6023","DOI":"10.1007\/s00500-018-3586-y","volume":"23","author":"S Sapre","year":"2019","unstructured":"Sapre S, Mini S (2019) Opposition-based moth flame optimization with Cauchy mutation and evolutionary boundary constraint handling for global optimization. Soft Comput 23(15):6023\u20136041","journal-title":"Soft Comput"},{"key":"6726_CR45","doi-asserted-by":"publisher","first-page":"103731","DOI":"10.1016\/j.engappai.2020.103731","volume":"94","author":"H Houssein Essam","year":"2020","unstructured":"Houssein Essam H, Saad MR, Hashim FA, Hassan Shaban M, Hassaballah. (2020) L\u00e9vy flight distribution: A new metaheuristic algorithm for solving engineering optimization problems. Eng Appl Artif Intell 94:103731","journal-title":"Eng Appl Artif Intell"},{"key":"6726_CR46","unstructured":"Sunayana A (2019) Deep learning approaches for detection of disease in potato and mango leaves. PhD diss., GB Pant University of Agriculture and Technology, Pantnagar-263145 (Uttarakhand)."}],"container-title":["Neural Computing and Applications"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-021-06726-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s00521-021-06726-9\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s00521-021-06726-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,11,16]],"date-time":"2023-11-16T02:03:29Z","timestamp":1700100209000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s00521-021-06726-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2022,1,21]]},"references-count":46,"journal-issue":{"issue":"9","published-print":{"date-parts":[[2022,5]]}},"alternative-id":["6726"],"URL":"https:\/\/doi.org\/10.1007\/s00521-021-06726-9","relation":{},"ISSN":["0941-0643","1433-3058"],"issn-type":[{"value":"0941-0643","type":"print"},{"value":"1433-3058","type":"electronic"}],"subject":[],"published":{"date-parts":[[2022,1,21]]},"assertion":[{"value":"10 April 2021","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"2 November 2021","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"21 January 2022","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare that they have no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"This article does not contain any studies with human or animal subjects performed by any of the authors.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Human and animal rights"}},{"value":"Informed consent does not apply as this was a retrospective review with no identifying patient information.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Informed consent"}}]}}